Content Reuse and Interest Sharing in Tagging Communities

TL;DR

This paper introduces metrics to measure user collaboration in tagging communities, revealing low levels of content reuse and shared interest that limit social knowledge harnessing, with implications for recommendation and reputation systems.

Contribution

It proposes two novel metrics for quantifying collaboration in tagging communities and applies them to show low collaboration levels in CiteULike and Connotea.

Findings

Low content reuse in communities

Limited shared interest among users

Implications for recommendation systems

Abstract

Tagging communities represent a subclass of a broader class of user-generated content-sharing online communities. In such communities users introduce and tag content for later use. Although recent studies advocate and attempt to harness social knowledge in this context by exploiting collaboration among users, little research has been done to quantify the current level of user collaboration in these communities. This paper introduces two metrics to quantify the level of collaboration: content reuse and shared interest. Using these two metrics, this paper shows that the current level of collaboration in CiteULike and Connotea is consistently low, which significantly limits the potential of harnessing the social knowledge in communities. This study also discusses implications of these findings in the context of recommendation and reputation systems.